Climate of Western and Central Equatorial Africa
Summary and Keywords
Western and Central Equatorial Africa (WCEA), home to the Congo rainforests, is the green heart of the otherwise dry continent of Africa. Despite its crucial role in the Earth system, WCEA’s climate variability has received little attention compared to the rest of Africa. Climate variability in the region is a result of complex interactions among various features acting on local and global scales. The mesoscale convective systems (MCSs) that have a preferentially westward propagation and present a distinct diurnal cycle are the main source of rainfall in the region. As a result of strong MCS activity, WCEA stands out as a convective anomaly within the tropics and experiences the world’s most intense thunderstorms as well as the highest lightning flash rates. The moisture of the region is supplied primarily from the Atlantic Ocean, with additional contributions from local recycling and East Africa. WCEA, in turn, serves as a moisture source for other parts of the continent.
One striking characteristic of WCEA is its intrinsic heterogeneity with respect to interannual variability of rainfall, resulting in delineation of the region primarily in the zonal direction. This is in contrast to the meridionally oriented spatial variability of the annual cycle and underlines the fact that driving factors of the two can be quite different. The annual cycle is mainly determined by the seasonal excursion of the sun. However, the interannual and intraseasonal variability of the region are modulated by remote forcings from all three oceans, reflected via zonal atmospheric cells and equatorial wave dynamics. The local atmospheric jets and regional Walker-like circulations also contribute to WCEA’s climate variability by modulating the moisture transport and vertical motion.
The region has experienced an increasing rate of deforestation in recent decades and has made a significant contribution to the global biomass burning emissions that can alter regional and global circulation, along with energy and water cycles. The mean annual temperature of the region has increased by about 1°C in the past 70 years. The annual rainfall over the same period presents a negative trend, though that is quite negligible in the eastern sector of the region.
Keywords: Congo rainforest, mesoscale convective systems, ITCZ, deforestation, atmospheric bridge, equatorial waves, African jets, African Walker cell, Congo air boundary, moisture advection and recycling
Western and Central Equatorial Africa (WCEA, 7E-32E and 10S-7N) contains the Congo lowland rainforest at the middle, surrounded by the East African Highlands (EAH), Southern African Highlands (SAH), and the Cameroon Highlands (Fig. 1).
WCEA lies just to the south of the Sahel and stretches along the Atlantic Ocean. Lake Victoria, the world’s largest tropical lake by area (Kitchell et al., 1997), and Lake Tanganyika, the world’s second deepest and largest lake by volume (Schubert et al., 2006) are located along the eastern boundaries of this region. Like other tropical landmasses, WCEA is generally identified as a region with high precipitation, warm temperature, and dense rainforests.
Nearly 20 percent of the global tropical rainforests are in Africa (ITTO, 2011), and 89 percent of these are distributed in the Congo Basin (Fig. 2), the world’s second largest contiguous forest after Amazonia (Mayaux et al., 2013).
Democratic Republic of the Congo (DRC), the largest country within WCEA, is the world’s second most forest-rich country after Brazil (ITTO, 2011). WCEA’s forests and savannas are a net carbon sink (Bombelli et al., 2009; Ciais et al., 2011; Fisher et al., 2013), and the carbon storage in intact forests of this area has increased in recent decades (Ciais et al., 2009; Lewis et al., 2009). The carbon uptake by forests and savannas are the primary contributors to this net carbon sink, whereas fires and deforestation are the main contributors to the carbon losses (Bombelli et al., 2009). Agricultural activities and forest degradation play a secondary role in carbon emissions. Most WCEA land is covered by evergreen forests (43 percent), located within its central latitudes, and savannas/woody savannas (46 percent), looping around these forests from north, east, and south (Fig. 2b). Cropland and natural vegetation mosaic include only 7 percent, and the inland waters about 2 percent of WCEA’s total area. The evergreen forests contain a much higher above-ground biomass than the savannas (Saatchi et al., 2011).
This region stands out as Africa’s largest contiguous forest region, receiving the highest amount of precipitation in the continent (Fig. 3a).
Two smaller areas with comparable rainfall totals are the Guinean Coast and the Ethiopian Highlands. The mean annual total of rainfall in most central parts of WCEA ranges between 1500 and 2000 mm, and over the highlands between 1000 and 1500 mm. However, the rainfall exceeds 2000 mm/year in about 8 percent of WCEA area: along the Atlantic Coast, in the eastern Congo Basin along the western edge of the EAH, and over Lake Victoria. These reflect the enhanced mesoscale convective systems (MCS) activity imposed by the effects of local geographical features (Jackson et al., 2009). WCEA is overall drier than the Amazon rainforest (e.g., Asefi-Najafabady & Saatchi, 2013). The spatial variability of annual mean surface air temperature over the region is overall smaller than that of the rest of the continent (Fig. 3b). However, the temperature variation over the highlands and along the areas with sharp topographic gradient is greater than other parts of WCEA. The mean temperature in the Congo rainforest is about 24.5°C, and it is generally lower than that of Amazonia, owing to its higher altitude (Malhi & Wright, 2004).
WCEA is one of the world’s most convectively active regions, particularly during the transition seasons when it dominates the global tropical circulation (Mohr et al., 1999; Liu & Zipser, 2005; Washington et al., 2013). The moisture advection from the Congo Basin modulates rainfall variability in various parts of Africa (Levin et al., 2009; van der Ent et al., 2010; Williams et al., 2012). The northern and southern parts of WCEA are a part of tropical Africa that is the world’s largest source of biomass burning (BB) emissions (Hauglustaine & Ehhalt, 2002; van der Werf et al., 2006, 2010). In addition to its health-related impacts, the BB alters atmospheric chemistry, radiative balance, clouds, and precipitation processes in regions within and well beyond Africa (Tosca et al., 2014, 2015; Hodnebrog et al., 2016; Zuidema et al., 2016).
The climate system in WCEA is, in turn, a result of complex interactions among various atmospheric, oceanic, and static geographical features, acting at regional to global scales. One of the striking characteristics of the region’s climate, arising from this inherent complexity, is its heterogeneity of interannual variability of rainfall (Nicholson, 1986; Balas et al., 2007; Dezfuli, 2011; Badr et al., 2016). This is in stark contrast to most other regions of Africa, including the Sahel and eastern equatorial Africa (Nicholson, 1996; Pohl & Camberlin, 2006; Hastenrath et al., 2011). Despite the crucial importance of understanding WCEA’s climate variability, this region has received relatively little attention, compared to other parts of Africa and the global tropical rainforests. This has been for a number of reasons, including the lack of in situ meteorological data, civil wars, and political conflicts in the region (Washington et al., 2006; Farnsworth et al., 2011; Malhi et al., 2013a).
This study provides an overview of our current understanding of climate in Western and Central Equatorial Africa. The climate drivers of the region are briefly presented in the next section and are discussed in greater detail throughout the subsequent sections. Various datasets from different sources have been used to present these features. Atmospheric variables, including winds, geopotential heights, and relative humidity (RH), are obtained from the National Centers for Environmental Prediction/Department of Energy (NCEP- DOE) Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis (aka Reanalysis 2, Kistler et al., 2001). Other datasets include the NOAA Extended Reconstructed sea-surface temperature (ERSST) V3 (Smith et al., 2008), surface temperature from V4.01 of the University of Delaware product using monthly global gridded high-resolution station-based data (Willmott et al., 2001), NASA Goddard Institute for Space Studies (GISS) surface temperature analysis for the globe (Hansen et al., 2005), and the NOAA Interpolated Outgoing Longwave Radiation (OLR; Liebmann & Smith, 1996). Two precipitation products are also used: the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product 3B42v7 (Huffman et al., 2010), and the Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis Version 7.0 (Schneider et al., 2015). The TMPA, which offers a reliable high-resolution rainfall product (Beighley et al., 2011; Munzimi et al., 2015) for this data-limited region, is used for presenting the climatology, annual cycle, and diurnal cycle, and the GPCC, which is available over a longer period, is used for trend analysis. Smoke-aerosol emissions are obtained from the Fire Energetics and Emissions Research version 1.0 (FEER.v1) product (Ichoku & Ellison, 2014), which is based on measurements of fire radiative power and aerosol optical thickness from the Moderate-resolution Imaging Spectro-radiometer (MODIS).
Overview of climate drivers
Various global, synoptic, and mesoscale phenomena contribute to WCEA’s weather and climate. It is the interaction between these features and regional geography that explains the diurnal, intraseasonal, interseasonal, interannual, and multiyear variability of WCEA’s climate. Some of these climatic features, which will be discussed in this article, are schematically shown in Figure 4.
The climate variability of the region can be directly or indirectly associated with the sea-surface temperature (SST) variability of the global tropical oceans (Todd & Washington, 2004; Okumura & Xie, 2006; Balas et al., 2007; Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). The western section of WCEA, stretching along the Atlantic Coast, is most strongly influenced by the local SST (e.g., Hirst & Hastenrath, 1983a; Nicholson & Entekhabi, 1986, 1987). Possible mechanisms include the impact of the SST on moisture advection or static stability of the lower troposphere. However, the relationship between local SST and rainfall may reflect a common remote forcing from the Pacific Ocean, which modulates the large-scale zonal atmospheric circulation (Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). This is primarily manifested via the El Niño-Southern Oscillation (ENSO) teleconnection, which varies spatially over WCEA, and sometimes it has opposite impacts on different parts of the region. In addition to regional heterogeneity within WCEA in response to the large-scale atmosphere–ocean system, the teleconnections can also be monthly specific (Balas et al., 2007).
At the regional scale, the meridional excursion of the Intertropical Convergence Zone (ITCZ) is associated with a bimodal annual cycle of rainfall, which is one of the climatic signatures of WCEA (e.g., Okoola & Ambenje, 2003; Washington et al., 2013). However, the ITCZ–rainfall paradigm alone cannot explain the interannual variability. The interaction between topography and three regional tropospheric jets also has to be incorporated (Nicholson & Grist, 2003; Nicholson, 2009; Pokam et al., 2012; Nicholson & Dezfuli, 2013). These are the low-level westerly (LLW) winds, the mid-tropospheric African easterly jet of the Northern (AEJ-N) and Southern Hemisphere (AEJ-S), and the upper-level tropical easterly jet (TEJ). The zonal winds also produce a Walker-like atmospheric circulation that acts at the intraseasonal time scale and is triggered by an interhemispheric pressure gradient and the zonal topographic gradient within the region (Dezfuli et al., 2015). The MCSs are generated along the region of sharp east–west topographic contrast at the western slopes of the Rift Valley highlands (Mohr et al., 1999; Liu & Zipser, 2005; Jackson et al., 2009). These systems have a preferential westward propagation toward the Congo Basin and are enhanced by the convectively coupled Kelvin waves approaching from the Atlantic Ocean (Nguyen & Duvel, 2008; Laing et al., 2011).
The MCSs produce the majority of rainfall in the region. As a result of strong MCS activity, the region experiences some of the world’s most intense thunderstorms and highest lightning frequency, although it receives less rainfall than equatorial regions of the Amazon and Indonesia (Mohr & Zipser, 1996a; Christian et al., 2003; Zipser et al., 2006; Collier & Hughes, 2011). This paradox has been attributed to differences in characteristics of thermodynamic stability, cloud physics, and regional atmospheric circulation in these regions (McCollum et al., 2000; Petersen & Rutledge, 2001; Liu et al., 2007).
In January, the zone of maximum continental precipitation appears just to the south of WCEA (10S-20S), although the region receives a considerable amount of rainfall over its southern sector (0-10S). As the year progresses, the maximum rainfall region migrates northward and occupies WCEA’s latitudes in April. It moves farther north until it reaches its northernmost location in July, which is the driest month in the southern half of WCEA. At this stage, the region of maximum rainfall starts marching southward, and in October it expands over WCEA. This bimodal seasonality of rainfall is traditionally attributed to the north–south migration of the ITCZ, which follows the sun. The ITCZ is commonly defined as an equatorial zone where the trade winds converge. The classic picture of the ITCZ is characterized by this near-surface convergence, which facilitates the ascent of thermally unstable moist air, resulting in deep convective clouds that produce heavy precipitation (Schneider et al., 2014). The ITCZ is also represented by low atmospheric surface pressure and high relative humidity, and is considered the ascending branch of the Hadley cell. Although this paradigm is primarily valid over the equatorial oceans (Xie & Philander, 1994; Kang et al., 2008; Donohoe et al., 2013), the ITCZ and the region of maximum rainfall can be decoupled over the continents (Nicholson, 2009; Žagar et al., 2011; Nicholson & Dezfuli, 2013). The trade winds, which are well developed over the oceans, can be interrupted over land. The equatorial precipitation over the continents is not simply a response to just the surface convergence. Rather, it can be modulated by a number of regional features such as local atmospheric jets, proximity to the oceans, terrain-induced convective systems, moisture recycling, and spatiotemporal variability of land cover and albedo. Moreover, at lower-troposphere, weak subsidence prevails during late evening hours, downslope over the WCEA’s plains (Jackson et al., 2009). Because of these shortcomings and the ambiguity in definition of the ITCZ, and the fact that this article focuses on the continental climate, here the term “ITCZ” is not used when referring to the zone of equatorial rainfall. Instead, the term “tropical rainbelt” (Kidson & Newell, 1977; Nicholson, 2008), or just simply the phrase “the region of maximum rainfall” will be used. The ITCZ will only be used to refer to the convergence zone by low-level winds.
We examine the strong annual cycle of rainfall in WCEA further, using an objective approach. This analysis is implemented by a recently developed open-source package in R, HiClimR, which is designed specifically for climate regionalization (Badr et al., 2014, 2015, 2016). The area is divided into three regions that are homogeneous with respect to the annual cycle of rainfall (Fig. 6a).
These subregions are separated in the meridional direction. The northernmost region, located mainly to the north of about 2N, represents a unimodal annual cycle (Fig. 6b); it receives the highest and lowest fractions of its annual totals during the August–September–October (32 percent) and December–January–February (5percent) seasons, respectively. The annual cycle of this region is similar to that of the Eastern Sahel but is shifted by one month. The southernmost region, which covers the area south of the equator, has a bimodal annual cycle with two peaks in March–April (23 percent) and November–December (28 percent). This region receives very little rainfall during June–July–August (6 percent). The central part of WCEA, located between these two, presents a transitional rainfall regime, bearing characteristics with similarities to the southern and northern regions. This region, with 1665 mm/year, has the highest annual total in WCEA, followed by the northern and southern sectors with 1555 and 1462 mm/year, respectively.
The rainiest two-month seasons of the entire WCEA are August–September in the north, September–October in the center, and November–December in the south, with the mean rainfall rates of 7.4, 6.8, and 6.6 mm/day, respectively. The range of rainfall amounts between the wettest and driest months is lowest in the central region (163 mm) after the southern (195 mm) and northern (218 mm) sectors. In parts of the WCEA with a bimodal regime, the rainfall total in boreal autumn is generally greater than in boreal spring. This is different from eastern equatorial Africa, which also has a bimodal annual cycle, but with more rainfall in March–April–May (MAM) than in October–November–December (OND). These two seasons, MAM and OND, are often referred to as “long rains” and “short rains,” respectively, in the climate terminology of eastern equatorial Africa (Nicholson, 1996; Camberlin & Philippon, 2002; Camberlin, 2016).
The diurnal variability of rainfall over the central part of the three regions (gray dashed boxes in Fig. 6a) with a coherent annual cycle is shown in Figure 6c. For each region, two rainy seasons are analyzed separately. Overall, a diurnal cycle is apparent in all cases, with minimum and maximum rainy hours occurring at 1000 and 1600 local standard time (LST), respectively, although a much weaker secondary peak can be identified at around 0400 LST. This primarily unimodal diurnal cycle is typical for the regions to the south of 10N (Nesbitt & Zipser, 2003; Mohr, 2004; Liu & Zipser, 2008). The precipitation rate in the main rainy months of the northern (August–September) and central (September–October) regions has a range of about 0.2–0.45 mm/hour between 1000 and 1600 LST. The maximum and minimum values for the southern region are slightly smaller. In both regions located in the Northern Hemisphere, the maximum rainfall intensity persists over the entire evening through 0100 LST, which is in fact the peak of onset of the rainy season (April–May) in the northernmost part of the area. In the southern region, however, the diurnal cycle of both rainy seasons, March–April and November–December, present very similar patterns, with the latter persistently having a higher rainfall intensity for all hours but 0100 LST. We can better understand the causes of the diurnal cycle by exploring the processes that are responsible for producing precipitation in the region.
Mesoscale rain-producing systems
Nearly all precipitation in the tropics is a result of convection, which includes a set of relatively small-scale thermally direct circulations driven by buoyancy forces that arise from static instability (Emanuel, 1994; Houze, 1997). The convection generates cumulonimbus clouds, which produce both convective and stratiform precipitation (Houze, 1997; Trapp, 2013). Clusters of these clouds can be grouped into different classes based on their size and brightness temperature (Mohr & Zipser, 1996b; Mohr et al., 1999). The most dominant systems of these rain-producing clouds in WCEA are MCSs. A mesoscale convective system is an organized ensemble of cumulonimbus clouds that interact to form a contiguous, extensive precipitation area on the order of 100 km or more in horizontal scale in at least one direction (Houze, 2004; Markowski & Richardson, 2011; Trapp 2013). The MCSs contribute to about 70–80 percent of the total rainfall in WCEA (Mohr et al., 1999; Schumacher & Houze, 2003; Nesbitt et al., 2006). Mohr et al. (1999) defined an MCS as a closed 250 K contour, with a contiguous minimum area greater than 2000 km2 and a minimum enclosed brightness temperature less than to 225 K. Other classes defined as variations of the MCS account for the remainder of the total rainfall in the region. These include large, warm clusters (LW), small, cold clusters (SC), and small, warm clusters (SW).
WCEA stands out as a convective anomaly within the tropics. The region has more intense thunderstorms than the equatorial land areas of Amazonia and Indonesia, and experiences the highest lightning flash rates in the global tropics (Toracinta & Zipser, 2001; Christian et al., 2003; Williams & Sátori, 2004; Zipser et al., 2006; Albrecht et al., 2016). The storms in WCEA are deeper (Geerts & Dejene, 2005) and more spatially expanded (Nesbitt et al., 2006) than those in other equatorial lands. Moreover, the largest contribution of the overshooting convection, defined as deep tropical convection with radar tops above 14 km, is found in this region (Liu & Zipser, 2005). Convection may be triggered by thermal forcing from elevated heat sources, low-level convergence, sea/land breezes, and wave dynamics. The MCSs in WCEA are primarily generated along the western slopes of the Rift Valley highlands and have a preferentially west-southwestward propagation toward the Congo Basin (Nguyen & Duvel, 2008; Laing et al., 2011). The propagation speed may depend on the size of the systems and shows some variability for different case studies. Nguyen and Duvel (2008) have found a westward speed of 12–20 m/s for the MCSs, with an equivalent radius of 200–500 km, whereas another study (Laing et al., 2011) has suggested a speed of 8–16 m/s, an average duration of about 18 hours for systems spanning over 673 km.
Despite being an anomalous convectively active region within the tropics, WCEA paradoxically receives less rainfall than Amazonia and the Maritime Continent (Williams & Sátori, 2004; Zipser et al., 2006). The reason for this counterintuitive observation is still a matter of open research, though a few studies have provided some possible explanations. McCollum et al. (2000), for example, attributed the rainfall asymmetry between WCEA and Amazonia primarily to differences in aerosols production and cloud-base height in the two regions. The large amount of aerosols in Africa due to enhanced fire activity results in smaller cloud droplet radii and hence reduction in precipitation efficiency. The cloud bases are higher in the Congo Basin than in Amazonia, and that increases the subcloud evaporation, which in turn is associated with lower relative humidity and rainfall. These higher cloud base heights may be a result of WCEA’s greater continentality, which is attributed to its higher elevation and to the synoptic-scale moisture transport (Williams & Sátori, 2004). The continental characteristic of WCEA was evident in the Williams and Satori study by showing that evaporation in the two basins is quite comparable, whereas the Congo Basin has a stronger insolation during the wet seasons. One implication of this finding is a relatively high ratio of sensible heat flux to latent heat flux in WCEA. Another important factor contributing to WCEA’s low rainfall is the relative aridity of the neighboring EAH and the role of high terrains in blocking moisture transport from the Indian Ocean (McCollum et al., 2000) and particularly from the Atlantic Ocean (Balas et al., 2007; Jackson et al., 2009; Dezfuli & Nicholson, 2013).
The MCSs present spatial and temporal variability within WCEA. Jackson et al. (2009) have examined various characteristics of MCSs over the region, including frequency of occurrence, diurnal cycle and annual cycle, associated volumetric and convective rainfall, and lightning activity. They showed that the mean climatology of MCS count and the volumetric rainfall produced by these systems have a similar spatial pattern, with a strong maximum in the central sector of the region. The seasonal cycle of these two is also closely comparable. It is worth noting that, despite the strong seasonality, WCEA is the only equatorial landmass with intense storms occurring in all seasons (Christian et al., 2003; Zipser et al., 2006). The percentage of convective rainfall, on the other hand, which ranges roughly between 60 and 80 percent, is relatively homogeneous throughout the region and remains fairly seasonally invariant. A clear diurnal cycle is evident in different MCS characteristics: both MCS frequency and ratio of convective rainfall have a maximum around 1500–1800 LST and a minimum between 0300 and 0900 LST, similar to diurnal cycle of the total rainfall shown in Figure 6c (Mohr, 2004; Futyan & Del Genio, 2007; Jackson et al., 2009; Vondou et al., 2010). The lightning flash rates also present a similar diurnal variation (Soula et al., 2016). The amount of rainfall per MCS, however, has an inverse relationship with these properties, that is, a maximum in nocturnal to morning hours and a minimum in afternoon to early evening hours (see Fig. 7b in Jackson et al., 2009). This reflects the contribution of lighter stratiform rainfall, which is dominant during the night and replaces the heavier convective rainfall (Nesbitt & Zipser, 2003).
WCEA has a warm temperature throughout the year, and unlike other parts of the continent it does not show strong seasonal variability (Fig. 7).
This is particularly evident over the Congo Basin, which has higher temperatures than the adjacent East African highlands in all seasons. Some seasonality, however, can be detected in the western sector of the region, confined between the Congo Basin and the Atlantic Ocean. The mean temperature in this area during July is several degrees cooler than in April. The HiClimR software has been used to objectively regionalize the area into homogeneous regions with respect to month-to-month variability of temperature (Fig. 8).
WCEA is divided into two subregions, both of which have a weak seasonal cycle (Fig. 8a). The temperature difference between the warmest month (March) and the coolest month (July) in the larger region that occupies the northern and western parts of WCEA is only 2.3°C (Fig. 8b). The smaller region, covering the southeastern sector of WCEA, reaches its lowest (21.8°C) and highest (23.7°C) temperatures during June–July and September, respectively. The southeastern area, relative to the rest of WCEA has smaller minimum, maximum, and mean monthly temperatures, and a lower seasonal variability.
Surface convergence: ITCZ and Congo Air Boundary
The long-term means of several atmospheric fields are shown in Figure 9.
These are provided for four months—January, April, July, and October—to examine the interseasonal variability and their relevance to various definitions of the ITCZ, discussed in Rainfall Patterns, and to precipitation climatology presented in Figure 5. An east–west oriented region of maximum convergence at 925 hPa appears where northeasterly and southerly/southwesterly winds meet (Fig. 9a). This zone that follows the seasonal migration of the sun extends over the northern parts of WCEA, in January. It then moves northward in April and July, when it reaches its northernmost location before it moves back southward in October, when its latitude is comparable to that in April. Throughout the three months, it remains to the north of WCEA. A secondary region of low-level convergence is observed over the East African Highlands and along the Congo Air Boundary (CAB), which is a zone where the Congo air stream and the winds from the Indian monsoon systems meet (Johnson, 1965; Hills, 1979; Nicholson, 1996; Tierney et al., 2011). The Congo air is humid and flows westerly and southwesterly, whereas the monsoon winds are northeasterly during winter and southeasterly during summer months. Unlike the Congo air, both monsoons are thermally stable and relatively dry (Nicholson, 1996). Isotopic composition analysis of East African waters has confirmed that the CAB separates these two air masses with different moisture contents (Levin et al., 2009).
OLR, vertical velocity, and relative humidity: a proxy for precipitation
Outgoing Longwave Radiation (OLR) and vertical velocity of the atmospheric column, particularly at the midtroposphere, can be used to infer the location and intensity of convective precipitation. Negative/positive values of omega (vertical velocity in pressure coordinates) and low/high values of OLR are associated with upward/downward motion, respectively. In fact, OLR is used to estimate the monthly precipitation in global gridded datasets (Xie & Arkin, 1998; Huffman et al., 2009). At synoptic scale, the OLR and vertical velocity are in good agreement (Kiladis et al., 2006; Fauchereau et al., 2009; Berhane et al., 2015).
The long-term mean patterns of OLR and vertically averaged (850–200 hPa) omega for four different months (January, April, July, and October) over Africa are shown in Figure 9b. The areas of minimum OLR and negative omega values within the equatorial latitudes are generally collocated. These areas appear over WCEA during the transition months of April and October, and move to the north and south of the region in July and January, respectively. This spatial variability is in good agreement with the bimodal seasonality of precipitation, shown in Figure 5. Some differences in details of the patterns can be detected, which may be due to the coarse resolution of the Reanalysis 2 product, compared to the TMPA data. In addition, the region in which the mean relative humidity of the troposphere reaches its maximum presents an interhemispheric seasonal excursion, and its pattern generally coincides with the rainbelt (Fig. 9c). However, the convergence regions representing the ITCZ and CAB (Fig. 9a) do not seem to exhibit similar patterns to the OLR, vertical velocity, and relative humidity.
Near-surface pressure patterns
The climatology patterns of near-surface (925 hPa) geopotential heights for different months (January, April, July, and October) are shown in Figure 9c. This allows us to identify the St. Helena High in the south tropical Atlantic. This semipermanent high-pressure cell is part of the global atmospheric circulation and appears at the descending branch of the Hadley cell between 27.5–30S and 5–10W. In comparison with the austral summer (January), in winter (July) the St. Helena High is stronger and moves equatorward (Wallace & Hobbs, 2006). This high-pressure cell controls the formation and variability of the low-level westerly/southwesterly flows, the Benguela jet (Nicholson, 2010), and the associated upwelling along the southeast Atlantic Coast (e.g., Lutjeharms & Meeuwis, 1987). The low-level winds contribute to development of the ITCZ and CAB as well as to the moisture transport to WCEA. Although the near-surface heights tend to be low in the ITCZ and rainbelt regions, their spatial patterns are quite different.
Based on various atmospheric fields discussed here and in the last two sections as well as previous studies, seasonal variability of the surface winds, ITCZ, CAB, and precipitation are schematically shown in Figure 9d. This schematic underscores the fact that the ITCZ and CAB are identified by low-level convergence and are not necessarily spatially coincident with the rainbelt over tropical Africa.
Moisture: advection and recycling
The moisture required for precipitation over the continents is supplied through advection from neighboring areas (lands or oceans) or from local recycling (Brubaker et al., 1993). The latter, described as the “recycling ratio,” is the fraction of surface evapotranspiration in a specified region that contributes to precipitation in the same region. Nearly two-thirds of the moisture transported from the oceans to lands is recycled, and the remainder returns to the oceans as runoff (Gimeno et al., 2010). The maximum recycling ratio in Africa occurs over WCEA, and it varies between 12 and 20 percent (Trenberth, 1999; Dirmeyer et al., 2009a; Makarieva et al., 2009; Spracklen et al., 2012). That underlines the strong coupling between soil moisture, recycling, and precipitation in the region (Dirmeyer et al., 2009b; Koster et al., 2004). The recycled moisture in WCEA serves as a water vapor source for the eastern sector of the region along the EAH (Mapande & Reason, 2005; Monaghan et al., 2012), as well as for the other parts of the continent, including the Sahel (van der Ent et al., 2010) and Ethiopian Highlands (Levin et al., 2009; Williams et al., 2012). The Congo Basin, in turn, receives moisture from East Africa (van der Ent et al., 2010). Disentangling the contributions of moisture recycling and atmospheric dynamics to the tropical rainfall is challenging and important for our understanding of regional climate variability at different time scales (Eltahir & Bras, 1996; Wohl et al., 2012; Makarieva et al., 2013; Washington et al., 2013). A number of studies have shown that the moisture content of the atmosphere alone does not determine the long-term rainfall variability in WCEA (Pokam et al., 2012; Dezfuli & Nicholson, 2013; Vizy & Cook, 2016). The specific humidity of the atmospheric column in rainy transition seasons of the region remains nearly unchanged during extreme wet and dry years (Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). This implies that the vertically integrated moisture flux convergence is more strongly associated with interannual variability of rainfall than is the air moisture content (Vigaud et al., 2007; Dezfuli & Nicholson, 2013; Vizy & Cook, 2016). This is in contrast to Southern Africa where changes in both moisture content and atmospheric circulation are important (Vizy & Cook, 2016).
High relative humidity is another characteristic of moisture in equatorial regions. In a previous section, OLR, Vertical Velocity and Relative Humidity: A Proxy for Precipitation, it was shown that the vertically averaged RH and rainfall have similar spatial patterns over WCEA in the presence of sufficiently strong upward motion. This is further analyzed in Figure 10, which demonstrates the seasonal variability of the vertical structure of RH and omega in the meridional direction.
The difference in these two fields between winter and summer is smallest along the equator, where the minimum contrast in seasonal precipitation is also observed. The RH in January has a maximum value at lower troposphere, decreases with height, reaches a local minimum at about 300 hPa, where it again increases with height, and reaches a second maximum at about 150 hPa. This bimodal vertical profile, which is a common characteristic of the moist deep convection in the tropical regions (Held et al., 1993; Mapes, 2001; Sherwood et al., 2010; Vergados et al., 2015), is a result of height variations in the water vapor lapse rate and the fractional detrainment rate (Romps, 2014). In July, although a bimodal pattern can be detected, it is not as clear as in January. The low-level maximum is divided at about 850 hPa, and the difference between upper-level maximum and minimum is quite weak. This may be due to the circulations imposed by the local atmospheric jets and the ITCZ, a similar paradigm to the West African Monsoon (WAM, Nicholson, 2009).
Regional atmospheric circulation
WCEA’s climate is greatly modulated by the variation of several regional atmospheric circulation features, with distinct characteristics in zonal, meridional, and vertical directions. This section provides an overview of the formation and impacts of these features, which often present a strong nonstationarity.
Meridional ascending/descending cells
The vertical cross section of omega in January (Fig. 10a) shows an ascending cell throughout the entire troposphere between the equator and 20S. The northern part of the region experiences a synoptic-scale area of descent in the middle to upper troposphere. During the month of July (Fig. 10b), a reverse pattern emerges: ascent in the Northern Hemisphere and descent in the Southern Hemisphere. The ascending cell in summer, however, is stronger and more latitudinally confined than that in winter. In this season, a secondary region of upward motion that is confined to low levels and associated with dry convection appears at about 15N. This area is coincident with the surface ITCZ and resembles the shallow meridional overturning generated by the Saharan Heat Low (SHL), which is often defined just to the west of this area (Sultan et al., 2003; Lavaysse et al., 2010; Engelstaedter et al., 2015). The patterns of vertical motion, as presented here and in previous sections, are closely associated with rainfall. However, this association is not limited to interseasonal variation. The intensity and expansion of ascending/descending atmospheric cells can also determine the interannual variability of rainfall (Kidson & Newell, 1977; Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013; Nicholson, 2015).
Regional atmospheric jets
Other factors including a set of atmospheric jets (Fig. 11) that exist at various vertical levels also contribute to the region’s climate variability by modulating the moisture transport, vertical motion, and wave dynamics.
These include the upper-level Tropical Easterly Jet (TEJ), midlevel African Easterly Jet of the Northern Hemisphere (AEJ-N) and the Southern Hemisphere (AEJ-S), and low-level westerly (LLW) wind maximum near the equator. The AEJ-N, which is perhaps known primarily for its crucial role in generating the African Easterly Waves (AEWs) and organized moist convection in the WAM system, develops in response to the meridional temperature gradient caused by the land–sea contrast between the warm Sahara and the cool Gulf of Guinea (e.g., Paradis et al., 1995; Hsieh & Cook, 2005; Hall et al., 2006). The AEJ-N is strongest during June–September, and its core appears at about 600 hPa, between 10 and 15N, with a maximum speed of 10–12 m/s. The AEJ-N is mainly a product of the shallow meridional circulation driven by the Saharan heat low and deep moist convection within the rainbelt, located equatorward of the jet (Thorncroft & Blackburn, 1999). However, other studies have suggested that the meridional gradient in soil moisture and associated land surface properties also exerts significant control on the jet (Cook, 1999; Wu et al., 2009). Although the jet is most active within the WAM region, its tail extends eastward within the longitude of WCEA (Fig. 11), and in some years it is manifested as a separate core from the western sector (Dezfuli & Nicholson, 2011). The AEWs that develop either from a mixed barotropic-baroclinic instability of the AEJ-N (Rennick, 1976; Thorncroft & Hoskins, 1994) or from some localized heating perturbations at the entrance region of the jet (Hall et al., 2006; Thorncroft et al., 2008) are observed to the north and south of the AEJ-N. The southern track of the AEWs trigger and organize rainfall into the mesoscale systems, some of which overlap with the northern latitudes of WCEA (Grist et al., 2002; Fink & Reiner, 2003; Kiladis et al., 2006).
The AEJ-N is recognizable throughout the year, though it weakens and moves equatorward between October and March, when its core is located between 0 and 5N, and its maximum speed reduces to 8 m/s compared to its peak in summer. The southern jet, the AEJ-S, however, is best discernible in August–November (Diedhiou et al., 1999; Nicholson & Grist, 2003). Its position varies between 10S and 5S at 600–700 hPa, and its maximum core speed is about 9 m/s in October. Although the AEJ-S is weaker and more zonally confined than the northern jet, its existence is also a result of the reversal of the surface temperature gradient. The maximum meridional temperature gradient is evident between the semiarid Kalahari to the south and the humid rainforest of WCEA to the north. Nicholson and Grist (2003) noted that the rainbelt during August–November, when both AEJs are present, is approximately bound by the axes of the two jets. The AEJ-S and its associated secondary circulation also play a role in aerosol transport off the continent (Adebiyi & Zuidema, 2016). This topic will be further discussed in the section Deforestation and Biomass Burning.”
Another important feature of the circulation in the region is the TEJ, which develops as a response to the intense meridional temperature gradient between the Himalayan Plateau and the Indian Ocean during boreal summer and extends to the African continent (Koteswaram, 1958). During the month of August, its maximum speed is about 16 m/s at 200 hPa and 8N along the western boundaries of WCEA (Fig. 11b). The jet’s left exit zone is collocated with the northern part of WCEA and may provide a mechanism of rainfall variability over that region (Nicholson & Grist, 2003). The westward extension of the TEJ over the WAM region seems to be at least partly a result of the Coriolis force acting on the equatorward outflow of deep convection just to the north of the jet (Thorncroft & Blackburn, 1999). The upper-level easterly flow is evident in the equatorial latitudes all year round. However, it is weak during the transition seasons when it crosses the equator, and it exhibits a secondary maximum during January and February when it reaches its southernmost position at around 7S (Nicholson & Grist, 2003). This secondary maximum speed of the easterly flow is usually not considered part of the TEJ; it is attributed to the equatorward branch of the upper-level flow that is deflected westward by the Coriolis force, a process similar to that suggested by Thorncroft and Blackburn (1999) for the Northern Hemisphere. The upper-level flow in transition seasons, although it is weaker than in boreal winter and summer, contributes strongly to rainfall variability by modulating the vertical motion by altering the upper-level divergence (Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013).
At lower troposphere, the LLW winds that are evident in all months to a varying degree (Fig. 9a) play an important role in the region’s rainfall variability. These winds are strong during years with above-normal rainfall in transition seasons, particularly within the northern coastal area of WCEA (Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). These low-level maximum winds are detected by various reanalysis products (Pokam et al., 2014) and sounding observations (Zhang et al., 2006). Their impact is manifested via moisture transport from the Atlantic Ocean or by triggering the uplift over the highlands, a prerequisite for the MCS formation (Matsuyama et al., 1994; Tazalika & Jury, 2008; Pokam et al., 2012; Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). The area with low-level vertical shear generated between the AEJ and LLW winds is coincident with the latitudinal expansion of maximum deep convection (Laing et al., 2011). The causes of these LLW flows will be discussed further in the following section.
Regional Walker-like circulations
A number of recent studies have examined the regional atmospheric circulation along the longitudinal-height plane over the equatorial Africa. Such overturning patterns are sometimes referred to as Walker-like circulations due to their similarity to the large-scale Walker cell over the equatorial Pacific Ocean (Wang, 2002; Lau & Yang, 2003). Most of these works have investigated the atmospheric overturning circulation between the Congo Basin and east equatorial Atlantic and its connection to rainfall in WCEA (Pokam et al., 2014; Cook & Vizy, 2015; Neupane, 2016). This is usually considered a weak regional Walker-like cell in the schematics of the global circulations (Webster, 1983). Dezfuli et al. (2015), however, have found a Walker-like circulation over the entire south equatorial Africa whose driving factors involve simultaneous changes in the southwestern Indian and north tropical Atlantic oceans (Fig. 12).
The LLW winds are perhaps the most important component of these circulation cells, and their formation mechanisms vary by season (Pokam et al., 2014). These have been attributed to the WAM system in boreal summer, when they reach the northern edge of WCEA (Fig. 9a). In other seasons, the LLW winds are well developed within WCEA latitudes, although they are weak in boreal spring (Pokam et al., 2012; Schwendike et al., 2014; Dezfuli et al., 2015). Pokam et al. (2014) have shown that the LLW winds in boreal spring and autumn (September–October–November, SON) form as a result of the contrast in diabatic heating between the equatorial Atlantic and WCEA. The ocean serves as a heat sink due to the enhanced radiative cooling at the top of the boundary layer clouds, whereas the equatorial land, including East Africa, turns to a heat source due to strong latent heat release. This zonal differential heating triggers ascending air over WCEA and descent over the ocean, forming an overturning circulation, which is stronger in the rainy season of SON than in MAM. This process is in contrast with previous studies suggesting that the South Atlantic anticyclone and the associated low-level Benguela jet (Nicholson, 2010) are responsible for formation of the LLW winds in the northern sector of WCEA (e.g., Fontan et al., 1992; Nicholson & Grist, 2003). The Congo-Atlantic zonal overturning circulation also occurs during boreal summer (Cook & Vizy, 2015; Neupane, 2016). A closed circulation, however, develops only in the presence of the Atlantic cold tongue, which sets up the favorable conditions for the subsiding branch of the cell (Cook & Vizy, 2015). The associated low-level temperature gradient can reach a maximum of about 6 K in July, resulting in LLW wind speeds of 3–4 m/s.
Examining daily atmospheric data during December–March, Dezfuli et al. (2015) have revealed a zonally overturning circulation over south equatorial Africa that explains the leading mode of synoptic-scale variability in the region. Termed zonal asymmetry pattern (ZAP), this mode of variability develops in the presence of a diagonal interhemispheric pressure gradient between the southwestern Indian and north tropical Atlantic oceans, and the zonal topographic contrast in equatorial Africa. The ZAP has positive and negative phases; key components of its positive phase are schematically shown in Figure 12. The circulation is triggered when LLW winds are generated in response to the cross equatorial pressure gradient. The ascending branch of the circulation develops when these winds hit the East African highlands. The upper-level component is primarily driven by outflow from the eastern convective branch. The associated upper-level convergence and lower-level divergence generate the subsiding component of the cell. The LLW flow and the ascending branch develop earlier and are stronger than the other two components. The mechanism of this overturning circulation relies on climatic communication between eastern and western equatorial Africa—two regions that are generally treated as climatically separate units. It is worth noting that the ZAP works reasonably independent from the teleconnections such as ENSO and other regional features such as tropical temperate troughs (TTTs). The TTTs that can be initiated by the Angola low are most active and associated with rainfall variability in Southern Africa, though the southern edge of the WCEA may also be occasionally affected by these systems (Lyons, 1991; Todd & Washington, 1999; Fauchereau et al., 2009; Manhique et al., 2011; Macron et al., 2014).
Remote drivers of WCEA climate
The climate variability in WCEA is a result of interactions between a large number of climatic features that act on regional to global scales. The characteristics of regional drivers and their contribution to WCEA climate variability were discussed in previous sections. In this section, an emphasis is given to changes in global SSTs and known tropical ocean-atmosphere teleconnections such as the ENSO, the Madden-Julian oscillation (MJO), tropical Atlantic variability, and Indian monsoon systems. These features that contribute to intraseasonal, interseasonal, and interannual variability of the region’s climate have different centers of action. Some of these phenomena that exist in the Atlantic and Indian oceans are schematically shown in Figure 4.
Global Walker circulations: atmospheric bridges
The SST changes in the Pacific Ocean and the associated Walker circulation can control the rainfall variability in remote areas, including WCEA. This occurs through the “atmospheric bridges” that reflect those changes by modulating the zonal atmospheric cells in the adjacent Indian and Atlantic oceans (Klein et al., 1999; Alexander et al., 2002, 2004; Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). The teleconnections are seasonally dependent and can vary within WCEA due to the strong heterogeneity of the region with respect to interannual variability (Balas et al., 2007; Dezfuli, 2011; Dezfuli & Nicholson, 2013). In their classic paper on the global impacts of the ENSO, Ropelewski and Halpert (1987) showed that the eastern part of WCEA is one of the regions in the African continent that presents a strong association with this phenomenon. Their results suggest that the rainfall over that region during the rainy boreal autumn and the following spring is enhanced/reduced during warm/cold phases of ENSO. This was confirmed by other studies that focused only on Africa and provided more details on this association (Nicholson & Kim, 1997; Camberlin et al., 2001). These studies found that the rainfall variability of the coastal region is also associated with ENSO, though in an opposite manner: less/more rainfall in warm/cold phases of ENSO. This was previously suggested by Nicholson and Entekhabi (1986, 1987) who showed that the ENSO and the coastal region’s rainfall have a similar quasi-periodic behavior during boreal spring.
A similar periodicity was also reported for the Congo Basin (Kazadi & Kaoru, 1996). The interannual relationship between the rainfall and global SSTs was further examined by Balas et al. (2007) who performed the analysis for five homogeneous regions of WCEA and for four different seasons, separately. They found that the SST–rainfall association is profoundly seasonally and regionally specific. For example, their results showed that while the Pacific Ocean is important during MAM, the rainfall variability of boreal summer is more strongly influenced by the SST changes in the Atlantic Ocean. Recognizing the intrinsic heterogeneity of the region, Dezfuli (2011) applied an objective regionalization approach and found that even the spatial configuration of the homogeneous regions varies by season. Built upon these findings, a follow-up analysis (Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013) used a modified version of the regions suggested by Dezfuli (2011) to study the underlying mechanisms. Two of the regions in the east and west of WCEA demonstrated strikingly opposite responses to the global SSTs and atmospheric circulation, particularly during OND (Fig. 13).
The central regions acted as a transition zone with very weak links to those features. They explained this via a remote forcing that is manifested as an atmospheric bridge and controls rainfall variability by modulating the location, size, and intensity of the east–west circulation cells. This mechanism is schematically shown in Figure 14.
The remote impact can also be manifested thermodynamically via tropospheric stabilization due to efficient redistribution of the latent heat within the equatorial atmosphere (Giannini et al., 2008).
Tropical Atlantic influence
The influence of the Atlantic Ocean on WCEA’s climate variability can be discussed in three contexts: direct impact of the tropical Atlantic features; the Pacific–Atlantic interaction; and the WCEA–Atlantic interaction.
The first aspect involves the SST changes in the Atlantic Ocean and the associated atmospheric circulations that are manifested in several climatic phenomena. These features, which have been extensively discussed in the literature (e.g., Zebiak, 1993; Carton et al., 1996; Ruiz-Barradas et al., 2000; Chang et al., 2000; Xie & Carton, 2004), mainly include the Atlantic Niño, the Atlantic cold tongue (ACT), the Atlantic meridional mode (AMM), the tropical southern Atlantic (TSA) Index, the tropical northern Atlantic (TNA) Index, the south Atlantic subtropical high (aka, St. Helena High), and the marine ITCZ. Some of these features are schematically shown in Figure 4. The impact of the SST changes in eastern equatorial Atlantic on rainfall variability of the coastal part of WCEA has been long recognized (e.g., Hirst & Hastenrath, 1983a,b; Hastenrath, 1984; Nicholson & Entekhabi, 1986, 1987; Okumura & Xie, 2006; Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). Warm/cold SSTs along the coast are associated with wet/dry conditions in the adjacent region. This has been explained through the thermodynamics consequences of the SST pertaining to the moisture content and static instability in the lower troposphere. The local SST variability has been attributed to various interrelated components of the tropical Atlantic variability. For example, during an Atlantic Niño, relaxation of the equatorial trade winds in the midbasin is associated with warm SST anomalies in the eastern basin. The intensity of the St. Helena high also contributes to the variability of the coastal SST. The AMM, whose positive phase is driven by SST increases in the TNA and decreases in the TSA, is a mode of variability in boreal summer that induces the LLW and the southeasterly trade winds. The state of the Atlantic SST that is manifested in various elements of the tropical Atlantic variability may contribute to equatorial wave activity that propagates to WCEA. This subject will be discussed further in Equatorial Waves and MJO.
The Atlantic Ocean also influences the climate variability of WCEA through interaction with the zonal atmospheric cells generated in the Pacific Ocean. It has been shown that in the coastal area of WCEA, the interannual variability of seasonal rainfall is more strongly associated with atmospheric parameters than with SSTs (Dezfuli & Nicholson, 2013; Nicholson & Dezfuli, 2013). This is intriguing because it implies that changes in both rainfall and SSTs reflect a common remote forcing from the Pacific Ocean that appears as an atmospheric bridge, as described in the last section.
The third aspect of the Atlantic involvement can be perceived within the framework of its role as the marine element of regional circulations, discussed in Regional Walker-like Circulations. For example, the northern component of the cross-equatorial pressure gradient required for the ZAP (Dezfuli et al., 2015) is closely related to the tropical Atlantic variability. The other regional Walker-like circulations (Pokam et al., 2014; Cook & Vizy, 2015; Neupane, 2016) affecting the LLW winds and precipitation over WCEA are also modulated by SST variability in the equatorial Atlantic.
Indian Ocean influence
Similar to the Atlantic Ocean, the contribution of the Indian Ocean to the climate of the region can be reflected through direct and indirect processes. The Pacific–WCEA teleconnection occurs indirectly by way of synchronous changes in the Indian Ocean. This may interact with the zonal atmospheric circulation associated with the Indian Ocean Dipole (IOD) mode, which is driven by opposite SST anomalies across the basin during September and October (Saji et al., 1999). The Indian Ocean is strongly dominated by the monsoon systems (Fig. 15), which are characterized by the low-level southwesterly Somali jet in boreal summer and the reversal northeasterly flow in boreal winter (e.g., Schott & McCreary, 2001; Schott et al., 2009).
Both summer and winter Indian monsoons provide easterly winds over East Africa, though those of the winter are slightly stronger. These can directly impact WCEA by moisture advection from the Indian Ocean through the East African Highlands (van der Ent et al., 2010). In addition, the easterly winds trigger convection through their contribution to the low-level convergence along the western edge of the highlands. The associated MCSs may propagate westward into the Congo Basin or develop the eastern component of the ZAP during boreal winter, as discussed in previous sections. The ZAP is also modulated by the intensity of the Mascarenes high in the southwestern Indian Ocean that communicates with its counterpart in the north equatorial Atlantic to generate the necessary interhemispheric pressure gradient.
Equatorial waves and MJO
Equatorial waves in the atmosphere are an important component of the intraseasonal variability of the climate. These waves can propagate and transfer energy in zonal and vertical directions within the tropics and generate oscillations in various atmospheric fields such as pressure, temperature, and winds (Wheeler & Nguyen, 2002). The equatorially trapped waves may in turn be triggered by the organized convective systems and can have an eastward or westward propagation, manifested primarily as Kelvin and Rossby waves, respectively. These waves may emerge as dry mode or be coupled to moist processes (Kiladis et al., 2009). The latter, known as the convectively coupled equatorial waves (CCEWs), have relatively slow propagation speed, compared to dry waves (e.g., Wheeler & Kiladis, 1999). These waves are closely related to the MJO (Madden & Julian, 1971) and are frequently observed within the convective envelope of the MJO (e.g., Kemball-Cook & Wang, 2001; Masunaga, 2007; Roundy, 2008). The MJO is the dominant planetary-scale episodic mode of intraseasonal (30–90 days) variability in the tropics, with an eastward propagation of about 5 m/s (Madden & Julian, 1971; Zhang, 2005). The intraseasonal variability of rainfall in the WCEA is dominated by a 20- to 70-day oscillation, resembling the MJO phase cycle (Gu, 2009; Sandjon et al., 2012, 2014a,b). The CCEWs serve as a mechanism that reflects the impacts of a remotely forced disturbance in an atmospheric field on rainfall variability in tropical Africa.
The majority of research on Africa has focused on the WAM system during July–August–September (JAS), some of which are relevant to the northern part of WCEA (e.g., Maloney & Shaman, 2008; Mekonnen et al., 2008; Janicot et al., 2009). Matthews (2004), for example, has shown that the negative convective anomalies over the Indo-Pacific warm pool associated with the MJO excite the Kelvin and Rossby waves, which propagate eastward and westward at a speed of about 33 m/s and 19 m/s, respectively. These waves meet over tropical Africa about 10 days later, and their accompanying cooling anomaly destabilizes the middle troposphere and induces convection. Over WCEA, the convectively coupled Kelvin waves (CCKWs) have a larger contribution to convective activity than the other types of equatorial waves, particularly during MAM when these waves explain about 15 percent of the total convection (Mekonnen & Thorncroft, 2016). However, the westward propagation of the MCSs may be attributed at least partly to the westward Inertia-Gravity (WIG) or equatorial Rossby (ER) waves (Kiladis et al., 2009; Tulich & Kiladis, 2012; Kamsu-Tamo et al., 2014). These MCSs are embedded in the eastward propagating CCKWs that originate in the equatorial Atlantic (Nguyen & Duvel, 2008; Sinclaire et al., 2015) and are most active during boreal spring. Laing et al. (2011) showed that the CCKWs have a phase speed of 12–22 m/s over equatorial Africa and modulate the convection during both rainy seasons of MAM and SON. However, these waves are more active in MAM, and during their study period (2000–2003) only 28 percent of the waves occurred in SON. Sinclaire et al. (2015) have examined the characteristics of the CCKWs over a long period (1979–2010) during the March–June season and showed that these waves present a strong interannual variability and precede the rainfall events over WCEA by about 4 days. For the same season, Berhane et al. (2015) have found that the CCEWs associated with the MJO convection originated in the Indian Ocean, reach the equatorial Africa about 20 days later, and modulate the regional convective activity. The position of the MJO’s convection center alters the LLW winds and their associated moisture advection to WCEA. The CCKWs also exist during boreal summer over WCEA, and these waves may propagate northeastward along the CAB and reach Ethiopian Highlands in about 2–4 days (Mekonnen & Thorncroft, 2016).
Deforestation and biomass burning
Tropical rainforests in WCEA have historically undergone relatively small changes, compared to Amazonia and Southeast Asia, primarily owing to low population density, political instability, and poor infrastructures in the region (ITTO, 2011; Megevand, 2013; Zhou et al., 2014). However, the increasing rates of deforestation in this region–doubling since 1990–underscores the fact that these forests may be at a turning point toward intensified deforestation and forest degradation rates (Achard et al., 2002; Simonian et al., 2010; ITTO, 2011; Megevand, 2013). Deforestation in the Congo Basin has been attributed to a number of factors such as increases in population and rapid urbanization. These factors will result in agricultural growth reducing the significant dependency of the countries in the region on imported food products. The rising rate of urbanization also increases the demand for wood fuel, which is the primary source of energy in most cities in WCEA. Other factors contributing to deforestation in the region include large-scale land acquisition for oil palm and cash crops, and growth in the mining industry.
Deforestation, as it may continue in the future, remains a critical issue because of its significant local and global effects. Modeling studies have shown that tropical deforestation generally results in warmer, drier conditions in WCEA, though the impacts can be monthly specific and vary spatially (Maynard & Royer, 2004; Roy et al., 2005; Werth & Avissar, 2005; Akkermans et al., 2014). Regional deforestation can induce the global climate system by increasing the CO2 release to the atmosphere and changing the surface albedo, evapotranspiration, and cloud physics processes (e.g., Lawrence & Vandecar, 2015; Bala et al., 2007). A recent modeling study has shown that the Congo Basin deforestation can also alter the WAM intensity and precipitation over the Sahel by not only modulating the moisture content of the air but also changing the circulation patterns (Nogherotto et al., 2013).
The forests in WCEA are bound by two regions of savannas/woody savannas to the north and south (Fig. 2b). These regions frequently experience fires that are primarily ignited by humans, making tropical Africa the world’s largest source of biomass burning emissions (Hauglustaine & Ehhalt, 2002; van der Werf et al., 2006, 2010). The mean total carbon emission rates are highest over savannas/woody savannas during the corresponding dry season of each region: JJA/DJF in southern/northern equatorial bands (Fig. 16).
Biomass burning in WCEA has profound local and global effects on human health and various climate processes (Tosca et al., 2014, 2015; Hodnebrog et al., 2016; Zuidema et al., 2016). Ichoku et al. (2016) have summarized in a conceptual schema (Fig. 17a) the possible interactions between various environmental processes in the northern sub-Saharan Africa with biomass burning.
Their conceptual model that is relevant to WCEA incorporates several components, including energy cycle, water cycle, land use, atmospheric chemistry, and their direct and indirect societal impacts. The regional circulation can also modulate lofting and advection of biomass burning aerosols. Adebiyi and Zuidema (2016) showed that about 55 percent of the BB aerosols that leave the southern Africa during September–October are transported westward by the AEJ-S to the south tropical Atlantic (Fig. 17b). The remaining aerosols are carried northwestward (8 percent) or returned to southern Africa (37 percent) via the midtropospheric anticyclone generated by the heat low over the Namib-Kalahari dryland. The AEJ-S also contributes to the efficiency of aerosol lofting by providing upward motion associated with the secondary circulation at the jet’s entrance. In addition, the smoke aerosols in the dry part of WCEA can spread out over the entire region and decrease the rainfall by reducing the effective cloud droplets size (Bréon et al., 2002; Sherwood, 2002; Williams & Sátori, 2004). This may partly explain the lower precipitation in WCEA than in Amazonia. Fire emission may also vary with the MJO phases (Zhang, 2013).
Trends in rainfall and temperature
This section discusses the trend and interannual variability of annual rainfall totals and mean temperature over WCEA for the period 1947–2013, based on the quality of available data. In the interest of presenting a concise discussion, the seasonal dependency of climate variability that was addressed in previous sections will not be addressed here.
The region’s strong spatial heterogeneity is manifested in annual rainfall variability (Fig. 18a).
WCEA is divided into five homogeneous regions with respect to the interannual variability of annual rainfall totals, using the HiClimR package (Badr et al., 2015). Although all regions show an overall negative trend for the entire period, the rainfall decrease in the eastern sector of WCEA is negligible (Fig. 18b). However, some discontinuities emerge when the time series are broken down into 15- to 20-year-long periods (e.g., Mahé et al., 2001; Laraque et al., 2001). The precipitation decline, most notably over the southern part of the Congo Basin (Yin & Gruber, 2010; Diem et al., 2014), has been attributed to the decrease of local moisture recycling due to deforestation and the large-scale ocean-atmospheric dynamics (Nogherotto et al., 2013; Lawrence & Vandecar, 2015). Despite the serious water deficit in WCEA in the past decade, the forests in this region have been significantly less affected than those in Amazonia, suggesting the potential adaptability of the forests in central Africa to short-term severe droughts (Asefi-Najafabady & Saatchi, 2013).
Unlike rainfall, the annual temperature does not show strong spatial heterogeneity (not shown). Except for a small area located in the southeastern corner of WCEA, the rest of the region is homogeneous with respect to the interannual variability of temperature. Consequently, WCEA is represented with one time series that shows the mean annual temperature over the entire region (Fig. 18c). A rising trend in the mean temperature is evident, as shown in previous studies (e.g., Kazadi & Kaoru, 1996; Samba et al., 2008), suggesting an approximately 1° C increase between mid-20th century and 2013. The temperature seems to have a 2- to 5-year periodicity, which has been shown (Samba et al., 2008) for the western sector of the region.
WCEA’s climate system is highly complex owing to the wide range of spatiotemporal scales of the contributing phenomena: the MCSs that are the main precipitation-producing systems of the region have a distinct diurnal cycle; the vertical motion and convective activity can be induced by global zonal circulation, equatorial waves, regional Walker-like cells, and local tropospheric jets; the mean annual cycle is associated with the seasonal excursion of the sun; topographical variation, proximity to the Atlantic and Indian oceans, and strong biomass burning emissions introduce additional anomalies to the climate of the region across various scales. The strong heterogeneity of the region’s interannual rainfall variability is one example reflecting the interactions among several climatic features. Despite the complexity of the WCEA’s climate, studies have been limited by the lack of in situ meteorological data due to long-lasting political instabilities and restricted data-sharing policies. Recent advances in satellite observations and climate models have facilitated climate studies for the region. However, lack of gauge-based data for validation raises some concerns regarding the use of these products and tools.
This article has discussed the evolution of our understanding of the WCEA’s climate drivers. Numerous useful resources are available for further details on theoretical background and other aspects of these features. Some of these include “Tropical meteorology, an introduction” (Krishnamurti et al., 2013), “Mesoscale-convective processes in the atmosphere” (Trapp, 2013), “Mesoscale meteorology in midlatitudes” (Markowski & Richardson, 2011), “The past, present and future of Africa's rainforests” (Malhi et al., 2013b), “African ecology: Benchmarks and historical perspectives. Springer Science & Business Media” (Spinage, 2012), “African climate and climate change: Physical, social and political perspectives” (Williams & Kniveton, 2011), Encyclopedia of atmospheric sciences, second edition (North et al., 2015) for general understanding of various atmospheric processes.
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